Quantifying Carbohydrate–Protein Interactions by Electrospray Ionization Mass Spectrometry Analysis
Bibliographic record
Abstract
The development of analytical methods capable of characterizing carbohydrate-protein interactions, which are critical for many biological processes, represents an active area of research. Recently, the direct electrospray ionization mass spectrometry (ESI-MS) assay has emerged as a valuable tool for identifying and quantifying carbohydrate-protein complexes in vitro. The assay boasts a number of strengths, including its simplicity, speed, low level of sample consumption, and the unique ability to directly probe binding stoichiometry and to measure multiple binding equilibria simultaneously. Here, we describe the implementation of the direct ESI-MS assay for the determination of carbohydrate-protein binding stoichiometries and affinities. Common sources of error encountered with direct ESI-MS analysis of carbohydrate-protein interactions are identified along with strategies for minimizing their effects. The application of ESI-MS and a catch-and-release strategy for carbohydrate library screening are also described. The utility of the direct ESI-MS assay can be extended by combining the technique with competitive protein or ligand binding. An overview of these "indirect" ESI-MS methods is given, as well as examples of recent applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".